Daily Science to all

On Green Energy: A Critical Look at LCOE

LCOE (Levelized Cost of Electricity) is the average calculated cost of electricity generation over the entire lifecycle of a power plant. It’s a key metric often cited to promote solar and wind energy projects. However, it’s worth looking beyond these abstract numbers.

If a salesperson for solar panels or wind turbines argues for the cost-effectiveness of renewable energy solely using LCOE, show them this graph:

The expenses for electricity transmission and distribution increase exponentially with the integration of renewable energy sources.

A look at the capital investments in the U.S. energy sector over the past 20 years reveals an interesting trend. Since 2008, investments in generation equipment—whether in thermal power plants (TPPs), nuclear power plants (NPPs), solar power plants (SPPs), or wind farms—have remained relatively stable, largely unaffected by the “green energy” trend.

Meanwhile, spending on electricity transmission and distribution has surged by 2.5–3 times. Even more significant costs emerge in low-voltage networks when implementing renewable energy systems. Installing rooftop solar panels, for instance, requires smart meters, robust transformers, upgrades to local distribution networks, and battery installations.

These costs are never accounted for in LCOE calculations but ultimately fall on the consumer, creating a hidden financial burden.

In essence, green energy calculations are often cleverly designed, but the reality—until a true technological breakthrough or “singularity” occurs—is that renewable energy remains more expensive. For now, nuclear power stands as the only truly sustainable and “green” energy source.

AI-Powered Headphones Create a “Sound Bubble” Around Users

Researchers from the University of Washington have unveiled innovative AI-enabled headphones that filter ambient noise, creating a “sound bubble” to shield users from unwanted sounds. The device employs six microphones and a neural network to amplify nearby sounds while suppressing distant ones within a range of up to 2 meters. This technology allows users to focus on conversations even in noisy environments, such as restaurants or parties. The team is now working on integrating this breakthrough into smaller devices, including hearing aids.

#science #tech

The top image shows the final results of the recent U.S. presidential election, won by Trump with a score of 312 to 226. Remarkably, no human could predict this outcome—not experts, super-forecasters, exit polls, prediction markets, nor even psychics. But the AI model ChatGPT-4o did, as shown in the bottom image, where it accurately forecasted a 309 to 229 outcome back in September at Wuhan University (yes, once again China and once again Wuhan).

The precision of this prediction is rooted in an extraordinary foundation. Instead of relying on real human opinions, the AI analyzed simulated “social replicas.” Two years ago, a breakthrough technology emerged, enabling the creation of algorithmic replicas of any social group. Astonishingly, these algorithms proved indistinguishable from real people in surveys. This discovery, sitting at the intersection of natural language processing, cognitive science, and sociology, offers enormous potential for social hacking.

In 2023, this technology evolved to create algorithmic replicas of citizens from any nation. While still far from achieving AGI, these systems now simulate the collective unconscious of entire societies. From this, I formulated two key hypotheses:

✔️ A paradigm shift transforming psychohistory into a practical science—one akin to Asimov’s fictional discipline that mathematically examines societal processes to accurately forecast the future.

✔️ A cultural phase shift ushering in a new era: algocognitive culture.

Now, just three months later—at a pace unimaginable before the age of technological singularity—researchers in Wuhan have provided experimental support that these hypotheses are not mere futurist speculation; they may indeed reflect reality.

In other words, it’s likely that our world has already undergone a profound transformation. The roles of humans and algorithms in science, culture, individual lives, and the “algorithmically enriched societies” of today will never be the same. What’s next? Let’s find out!

#AIRevolution #CognitiveScience #FutureSociety
#science

Australian mathematicians have debunked the theorem suggesting that if a monkey were given infinite time with a typewriter, it would eventually produce all of Shakespeare’s works.

Scientists calculated that even if all 200,000 chimpanzees on Earth were made immortal and typed continuously, they still wouldn’t complete Shakespeare’s works before the end of the universe. They based their calculations on the prediction that our universe will cease to exist in a googol years (a number with 100 zeros) according to the heat death theory. Moreover, they didn’t take into account how these typing monkeys would survive the Sun’s eventual engulfment of Earth, expected to happen in a few billion years.

The mathematicians noted that a single chimpanzee would only have a 5% chance of typing the word “banana” in its lifetime. And the probability of a monkey producing a coherent sentence like “I am a chimpanzee, therefore I exist” is one in 10 million billion billion. Shakespeare’s complete works, in comparison, contain 884,647 words.

So, while the theorem holds true in abstract mathematics, it is misleading, as it’s practically unachievable due to the constraints of our actual universe.

#Mathematics #science #MonkeyTheorem

Money begets money, success begets success, and Nobels beget Nobels.

Believe it or not, according to Nature, 95% of Nobel laureates (702 out of 736) belong to a single vast academic family tree, a network that I reflects their academic “lineage.” This isn’t just biological; it’s about mentorship—one scientist guiding another, usually as an advisor or mentor. Only a rare few, just 32 laureates, somehow achieved the Nobel without being part of this formidable academic network (you can see them on the left side of the network diagram).

Inside this colossal network lie 33 generations of laureates, all tracing their academic roots back to one progenitor—Erasmus of Rotterdam (1466–1536). He pioneered a system of mentorship that laid the foundation for today’s structured guidance, where knowledge, skills, connections, and experience are passed from one scientist to another, often leading to the highest accolades in science, such as the Nobel.

Opinion:

Success in a scientific career is not so much a matter of talent and hard work, but of connections and prestige.

1. Mentorship is the key driver behind the rise of superstars.
2. Elite mentorship propels scientists to the highest echelons of success.
3. The most critical factor in elite career trajectories isn’t just talent, and it’s not mere luck. It’s specific luck: the luck of having the right mentor.

Thus, superstars are born through mentorship.

Now, after Nature’s publication, the “Mentor Effect” in the “science of success” has earned experimental validation.

Take note, parents and grandparents: where—and with whom—your children and grandchildren learn can shape their paths in ways you might never expect.

Here are some relevant hashtags for your post:

#Science #NobelPrize

🚀 SpaceX to Attempt First-Ever Starship-to-Starship Refueling in March 2025

NASA has announced that SpaceX will conduct a groundbreaking test of orbital fuel transfer between two Starship spacecraft as early as March next year. This in-orbit refueling demonstration is crucial, as it could enable larger payload deliveries beyond Earth’s orbit and support future unmanned missions. Should the test succeed, SpaceX is set to land astronauts on the Moon in September 2026.

#SpaceX #Starship #NASA #SpaceExploration #OrbitalRefueling #MoonMission #FutureOfSpace #TechNews #Science

🚀 China Successfully Tests Supersonic Passenger Jet

The Chinese company Space Transportation has completed successful tests on a passenger jet that can reach speeds of up to Mach 4—twice as fast as the iconic Concorde, which retired in 2003.

According to the company, this revolutionary jet could take passengers from Beijing to New York in just two hours. The first commercial flight is expected as early as 2027, promising a new era in high-speed travel.

#Aviation #SupersonicFlight #science

A Strong Contender for the Next Nobel Prize

The startup Iambic has made a breakthrough that surpasses Google DeepMind’s AlphaFold. While AlphaFold, the AI system developed by Google DeepMind, recently earned a Nobel Prize in Chemistry for predicting the 3D structure of how molecules bind to target proteins, this is just the beginning. It’s impressive but not enough to drastically reduce the time (10-15 years) and costs ($1-2.6 billion per drug) required to bring new medicines to market.

Iambic has taken it a step further by developing an AI model that predicts, with remarkable accuracy, how well a human body will absorb a specific drug candidate. The predictions are validated against real-world data, making it a promising tool for pharmaceutical development.

The success of a drug candidate depends on several key properties—pharmacokinetics, efficacy, and toxicity. These are exactly the factors predicted by Iambic’s AI-powered drug discovery platform called Enchant, which boasts a predictive accuracy of 0.74, compared to just 0.58 achieved by previous models.

The Enchant model could potentially cut the costs of drug development in half, allowing pharmaceutical companies to assess a drug’s potential success at the earliest stages of research.

To understand the significance of Iambic’s breakthrough, consider the vast competition in the “AI in Biomedicine” sector, where more than 8,600 companies are racing to unlock the next major innovation (as shown in the chart above). In the sub-segment of “AI-based Analytics Platforms for Drug Development” alone, the number of companies has grown fourfold in the last three years, now standing at 950 competitors (see the chart below).

#AI #DeepPharma #DrugDiscovery #Biotech #Pharmacology #AlphaFold
#science

A Strong Contender for the Next Nobel Prize

The startup Iambic has made a breakthrough that surpasses Google DeepMind’s AlphaFold. While AlphaFold, the AI system developed by Google DeepMind, recently earned a Nobel Prize in Chemistry for predicting the 3D structure of how molecules bind to target proteins, this is just the beginning. It’s impressive but not enough to drastically reduce the time (10-15 years) and costs ($1-2.6 billion per drug) required to bring new medicines to market.

Iambic has taken it a step further by developing an AI model that predicts, with remarkable accuracy, how well a human body will absorb a specific drug candidate. The predictions are validated against real-world data, making it a promising tool for pharmaceutical development.

The success of a drug candidate depends on several key properties—pharmacokinetics, efficacy, and toxicity. These are exactly the factors predicted by Iambic’s AI-powered drug discovery platform called Enchant, which boasts a predictive accuracy of 0.74, compared to just 0.58 achieved by previous models.

The Enchant model could potentially cut the costs of drug development in half, allowing pharmaceutical companies to assess a drug’s potential success at the earliest stages of research.

To understand the significance of Iambic’s breakthrough, consider the vast competition in the “AI in Biomedicine” sector, where more than 8,600 companies are racing to unlock the next major innovation (as shown in the chart above). In the sub-segment of “AI-based Analytics Platforms for Drug Development” alone, the number of companies has grown fourfold in the last three years, now standing at 950 competitors (see the chart below).

#AI #DeepPharma #DrugDiscovery #Biotech #Pharmacology #AlphaFold
#science

Water in Zero Gravity! 🚀
Astronaut Don Pettit demonstrates the wonders of microgravity by injecting dye into a floating water sphere aboard the International Space Station (ISS). Without gravity, the water takes on a perfect spherical shape, revealing the fascinating behavior of fluids in space. 🌌💧

#Science #Microgravity #FluidDynamics #ISS #Astronomy #Physics #DonPettit #ScienceIsCool #STEM #SpaceExploration

A Strange Spider Within a Spider: Cyclosa’s Astonishing Decoy

Something large and bizarre, seemingly assembled from whatever was available – web threads, debris, and remnants – isn’t a creature of nightmares. It’s a decoy.

The real spider, much smaller (only about 5 mm), hides beneath the “abdomen” of its intimidating counterpart.

These clever decoys are crafted by spiders of the Cyclosa genus from the orb-weaver family (Araneidae). Typically, the real spider positions itself on the edge of the web, subtly pulling on the silk threads. This causes the fake spider to move, creating the illusion of a living, menacing predator from afar.

The decoy itself is a masterpiece of recycling. Cyclosa spiders construct it from leaf fragments, leftover egg sacs, and the desiccated bodies of previous victims. These creations serve as a diversion, tricking predators like paper wasps, birds, or lizards into attacking the decoy instead of the spider. This distraction gives the real spider precious time to escape.

There’s also a hypothesis that these web decorations attract more prey. Organic debris on the web hosts yeast-like fungi, which release chemicals that lure insects into the trap, increasing Cyclosa’s hunting success.

#Science #Biology #Arachnology #Spiders #Nature #Evolution #Insects #Survival #Decoy